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Record W1992076502 · doi:10.3905/jai.2002.319064

Large versus Small Hedge Funds

2002· article· en· W1992076502 on OpenAlexaff
Greg N. Gregoriou, Fabrice Douglas Rouah

Bibliographic record

VenueThe Journal of Alternative Investments · 2002
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsMotor imagerySensorimotor rhythmPsychologyPhysical medicine and rehabilitationRhythmElectroencephalographyPopulationAthletesPhysical therapyMedicineBrain–computer interfaceNeuroscience

Abstract

fetched live from OpenAlex

<h3>Abstract</h3> Previous psychological studies using questionnaires have consistently reported that athletes have superior motor imagery ability, both for sports-specific and sports non-specific movements. However, regarding motor imagery of sports non-specific movements, no physiological studies have demonstrated differences in neural activity between athletes and non-athletes. The purpose of the present study was to examine differences in bioelectric sensorimotor rhythms during kinesthetic motor imagery (KMI) of sports non-specific movements between gymnasts and non-gymnasts. We selected gymnasts as an example population because they are likely to have particularly superior motor imagery ability due to frequent usage of motor imagery including KMI as part of daily practice. Healthy young participants (16 gymnasts and 16 non-gymnasts) performed repeated motor execution and KMI of sports non-specific movements (wrist dorsiflexion and shoulder abduction of the dominant hand). Scalp electroencephalogram (EEG) was recorded over the contralateral sensorimotor cortex. During motor execution and KMI, sensorimotor EEG power is known to decrease in the α- (8–15 Hz) and β-bands (16–35 Hz), referred to as event-related desynchronization (ERD). We calculated the maximal peak of ERD both in the α- (αERDmax) and β-bands (βERDmax) as a measure of changes in corticospinal excitability. αERDmax was significantly greater in gymnasts, who subjectively evaluated their KMI as being more vivid, for both KMI tasks. On the other hand, βERDmax was greater in gymnasts only for shoulder abduction KMI. These findings suggest gymnasts’ signature of flexibly modulating sensorimotor rhythm with no movements, which may be the basis of their superior ability of KMI for sports non-specific movements. <h3>New &amp; Noteworthy</h3> Kinesthetic motor imagery of sports non-specific movements was compared between gymnasts and non-gymnasts (i.e., healthy controls) from both physiological and psychological approaches. The EEG sensorimotor rhythms during kinesthetic motor imagery were more desynchronized in gymnasts who subjectively imaged their own movements as being more vivid. The work reveals novel ability in gymnasts to flexibly control their sensorimotor rhythms with no actual movements, which would be the basis of their superior ability of motor imagery.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.131
GPT teacher head0.360
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations58
Published2002
Admission routes1
Has abstractyes

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